diff --git a/cpp/benchmarks/io/parquet/parquet_reader_input.cpp b/cpp/benchmarks/io/parquet/parquet_reader_input.cpp
index 7563c823454..ce115fd7723 100644
--- a/cpp/benchmarks/io/parquet/parquet_reader_input.cpp
+++ b/cpp/benchmarks/io/parquet/parquet_reader_input.cpp
@@ -32,7 +32,8 @@ constexpr cudf::size_type num_cols = 64;
 void parquet_read_common(cudf::size_type num_rows_to_read,
                          cudf::size_type num_cols_to_read,
                          cuio_source_sink_pair& source_sink,
-                         nvbench::state& state)
+                         nvbench::state& state,
+                         size_t table_data_size = data_size)
 {
   cudf::io::parquet_reader_options read_opts =
     cudf::io::parquet_reader_options::builder(source_sink.make_source_info());
@@ -52,7 +53,7 @@ void parquet_read_common(cudf::size_type num_rows_to_read,
     });
 
   auto const time = state.get_summary("nv/cold/time/gpu/mean").get_float64("value");
-  state.add_element_count(static_cast<double>(data_size) / time, "bytes_per_second");
+  state.add_element_count(static_cast<double>(table_data_size) / time, "bytes_per_second");
   state.add_buffer_size(
     mem_stats_logger.peak_memory_usage(), "peak_memory_usage", "peak_memory_usage");
   state.add_buffer_size(source_sink.size(), "encoded_file_size", "encoded_file_size");
@@ -231,6 +232,70 @@ void BM_parquet_read_chunks(nvbench::state& state, nvbench::type_list<nvbench::e
   state.add_buffer_size(source_sink.size(), "encoded_file_size", "encoded_file_size");
 }
 
+template <data_type DataType>
+void BM_parquet_read_wide_tables(nvbench::state& state,
+                                 nvbench::type_list<nvbench::enum_type<DataType>> type_list)
+{
+  auto const d_type = get_type_or_group(static_cast<int32_t>(DataType));
+
+  auto const n_col           = static_cast<cudf::size_type>(state.get_int64("num_cols"));
+  auto const data_size_bytes = static_cast<size_t>(state.get_int64("data_size_mb") << 20);
+  auto const cardinality     = static_cast<cudf::size_type>(state.get_int64("cardinality"));
+  auto const run_length      = static_cast<cudf::size_type>(state.get_int64("run_length"));
+  auto const source_type     = io_type::DEVICE_BUFFER;
+  cuio_source_sink_pair source_sink(source_type);
+
+  auto const num_rows_written = [&]() {
+    auto const tbl = create_random_table(
+      cycle_dtypes(d_type, n_col),
+      table_size_bytes{data_size_bytes},
+      data_profile_builder().cardinality(cardinality).avg_run_length(run_length));
+    auto const view = tbl->view();
+
+    cudf::io::parquet_writer_options write_opts =
+      cudf::io::parquet_writer_options::builder(source_sink.make_sink_info(), view)
+        .compression(cudf::io::compression_type::NONE);
+    cudf::io::write_parquet(write_opts);
+    return view.num_rows();
+  }();
+
+  parquet_read_common(num_rows_written, n_col, source_sink, state, data_size_bytes);
+}
+
+void BM_parquet_read_wide_tables_mixed(nvbench::state& state)
+{
+  auto const d_type = []() {
+    auto d_type1 = get_type_or_group(static_cast<int32_t>(data_type::INTEGRAL));
+    auto d_type2 = get_type_or_group(static_cast<int32_t>(data_type::FLOAT));
+    d_type1.reserve(d_type1.size() + d_type2.size());
+    std::move(d_type2.begin(), d_type2.end(), std::back_inserter(d_type1));
+    return d_type1;
+  }();
+
+  auto const n_col           = static_cast<cudf::size_type>(state.get_int64("num_cols"));
+  auto const data_size_bytes = static_cast<size_t>(state.get_int64("data_size_mb") << 20);
+  auto const cardinality     = static_cast<cudf::size_type>(state.get_int64("cardinality"));
+  auto const run_length      = static_cast<cudf::size_type>(state.get_int64("run_length"));
+  auto const source_type     = io_type::DEVICE_BUFFER;
+  cuio_source_sink_pair source_sink(source_type);
+
+  auto const num_rows_written = [&]() {
+    auto const tbl = create_random_table(
+      cycle_dtypes(d_type, n_col),
+      table_size_bytes{data_size_bytes},
+      data_profile_builder().cardinality(cardinality).avg_run_length(run_length));
+    auto const view = tbl->view();
+
+    cudf::io::parquet_writer_options write_opts =
+      cudf::io::parquet_writer_options::builder(source_sink.make_sink_info(), view)
+        .compression(cudf::io::compression_type::NONE);
+    cudf::io::write_parquet(write_opts);
+    return view.num_rows();
+  }();
+
+  parquet_read_common(num_rows_written, n_col, source_sink, state, data_size_bytes);
+}
+
 using d_type_list = nvbench::enum_type_list<data_type::INTEGRAL,
                                             data_type::FLOAT,
                                             data_type::DECIMAL,
@@ -272,6 +337,24 @@ NVBENCH_BENCH(BM_parquet_read_io_small_mixed)
   .add_int64_axis("run_length", {1, 32})
   .add_int64_axis("num_string_cols", {1, 2, 3});
 
+using d_type_list_wide_table = nvbench::enum_type_list<data_type::DECIMAL, data_type::STRING>;
+NVBENCH_BENCH_TYPES(BM_parquet_read_wide_tables, NVBENCH_TYPE_AXES(d_type_list_wide_table))
+  .set_name("parquet_read_wide_tables")
+  .set_min_samples(4)
+  .set_type_axes_names({"data_type"})
+  .add_int64_axis("data_size_mb", {1024, 2048, 4096})
+  .add_int64_axis("num_cols", {256, 512, 1024})
+  .add_int64_axis("cardinality", {0, 1000})
+  .add_int64_axis("run_length", {1, 32});
+
+NVBENCH_BENCH(BM_parquet_read_wide_tables_mixed)
+  .set_name("parquet_read_wide_tables_mixed")
+  .set_min_samples(4)
+  .add_int64_axis("data_size_mb", {1024, 2048, 4096})
+  .add_int64_axis("num_cols", {256, 512, 1024})
+  .add_int64_axis("cardinality", {0, 1000})
+  .add_int64_axis("run_length", {1, 32});
+
 // a benchmark for structs that only contain fixed-width types
 using d_type_list_struct_only = nvbench::enum_type_list<data_type::STRUCT>;
 NVBENCH_BENCH_TYPES(BM_parquet_read_fixed_width_struct, NVBENCH_TYPE_AXES(d_type_list_struct_only))